Machine Learning Principal Solutions Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Principal Solutions Architect based in the United States.

This role offers the opportunity to lead complex AI and machine learning initiatives for enterprise clients while shaping the future of intelligent data solutions.

You will take ownership of strategic ML architecture, from initial vision and design through deployment, optimization, and long-term operations.

The position combines deep technical expertise, consulting leadership, and customer partnership to deliver measurable business outcomes.

You will collaborate with data scientists, engineers, platform teams, and executive stakeholders to build scalable AI solutions.

This role provides significant influence in defining best practices, advancing AI capabilities, and driving innovation across client engagements.

You will join a remote-first, high-performing environment where autonomy, technical excellence, and continuous learning are highly valued.

Accountabilities

• Lead the end-to-end architecture, implementation, and lifecycle management of AI and machine learning solutions for strategic client engagements.
• Own solution design and delivery across the full ML lifecycle, including model development environments, deployment strategies, monitoring, retraining, and production operations.
• Translate complex business objectives and data science requirements into secure, scalable, and resilient technical architectures.
• Design and optimize environments that enable data scientists and engineers to build, train, test, and deploy machine learning models using client data.
• Build and maintain robust data pipelines by integrating information from multiple sources and preparing data environments for analytics and ML applications.
• Define production infrastructure, deployment approaches, and operational strategies to ensure reliable consumption and maintenance of AI solutions.
• Partner with data scientists to transform data into actionable insights and production-ready machine learning models.
• Develop testing, quality assurance, validation, and monitoring strategies to ensure solution reliability, performance, and observability.
• Collaborate with Sales and account leadership to support client growth, identify new opportunities, and strengthen long-term partnerships.
• Serve as a trusted technical advisor to senior and executive stakeholders, guiding AI/ML roadmaps and strategic decisions.
• Lead architecture discussions, discovery workshops, technical reviews, and complex problem-solving sessions with clients.
• Act as a technical escalation point for challenging AI/ML initiatives and ensure successful project outcomes.
• Contribute to internal AI/ML capabilities through reusable frameworks, accelerators, reference architectures, documentation, and best practices.
• Mentor engineers, data scientists, and technical team members to strengthen consulting and delivery expertise.

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• Help establish scalable delivery standards while promoting customer success, innovation, and technical excellence.
  
  

Requirements

• 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, Data Scientist, or similar technical role building and deploying production-scale data and ML solutions.
• Strong expertise in programming languages such as Python, Scala, Java, or similar, including experience developing APIs and web applications using frameworks such as Flask, Django, or Spring.
• Proven ability to design, build, and operate complex data pipelines using SQL, distributed queries, and various data processing technologies.
• Hands-on experience with big data and analytics platforms such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar technologies.
• Experience working with diverse data sources including databases, messaging systems, data warehouses, and enterprise platforms.
• Strong understanding of cloud architecture, networking concepts, Linux-based systems, and modern storage and compute platforms.
• Demonstrated experience deploying machine learning models into production environments with focus on scalability, reliability, security, and performance.
• Strong understanding of the complete software development lifecycle, including architecture, documentation, development, testing, deployment, and operations.
• Experience working directly with customers in consulting, professional services, or client-facing technology environments.
• Proven ability to manage pre-sales activities, project scoping, account growth initiatives, and technical discovery.
• Strong analytical thinking with the ability to break down complex, ambiguous problems into structured solutions.
• Excellent communication and presentation skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• Experience collaborating with distributed teams across Sales, Engineering, Data Science, Product, and business stakeholders.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• Preferred experience with cloud and AI ecosystems such as AWS, Azure, GCP, Snowflake, Databricks, or similar platforms.
• Preferred experience with ML frameworks and tools including TensorFlow, Keras, scikit-learn, H2O, MLflow, AWS SageMaker, or Azure ML.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes is a plus.
• Experience in consulting environments or contributing to technical communities, open-source projects, publications, or industry events is beneficial.
  
  

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Benefits

• Remote-first work environment with flexibility to collaborate across distributed global teams.
• Competitive compensation package with comprehensive employee benefits.
• 401(k) plan with company matching.
• Dental and vision insurance coverage.
• Home office equipment stipend to support remote productivity.
• Annual learning and development stipend to support professional growth.
• Four weeks of paid time off plus company holidays.
• Opportunity to work on impactful AI and data transformation projects with leading organizations.
• Access to challenging technical projects, mentorship, and career development opportunities.
• Collaborative culture focused on transparency, autonomy, innovation, and continuous improvement.
• Inclusive workplace environment committed to diversity, belonging, and equal opportunity.
  
  

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.